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Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington's disease.

ABSTRACT: Currently, there are no therapies available to modify the disease progression of Huntington's disease (HD). Recent clinical trial failures of antisense oligonucleotide candidates in HD have demonstrated the need for new therapeutic approaches. Here, we developed a novel in-silico fragment scanning approach across the surface of mutant huntingtin (mHTT) polyQ and predicted four hit compounds. Two rounds of compound analoging using a strategy of testing structurally similar compounds in an affinity assay rapidly identified GLYN122. In vitro, GLYN122 directly binds and reduces mHTT and induces autophagy in neurons. In vivo, our results confirm that GLYN122 can reduce mHTT in the cortex and striatum of the R/2 mouse model of Huntington's disease and subsequently improve motor symptoms. Thus, the in-vivo pharmacology profile of GLYN122 is a potential new preclinical candidate for the treatment of HD.

SUBMITTER: Galyan SM

PROVIDER: S-EPMC9668931 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington's disease.

Galyan Simon Marius SM Ewald Collin Y CY Jalencas Xavier X Masrani Shyam S Meral Selin S Mestres Jordi J

Scientific reports 20221116 1

Currently, there are no therapies available to modify the disease progression of Huntington's disease (HD). Recent clinical trial failures of antisense oligonucleotide candidates in HD have demonstrated the need for new therapeutic approaches. Here, we developed a novel in-silico fragment scanning approach across the surface of mutant huntingtin (mHTT) polyQ and predicted four hit compounds. Two rounds of compound analoging using a strategy of testing structurally similar compounds in an affinit ...[more]

PMID: 36385140

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Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington's disease.

Publications

Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington's disease.

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